Military, such as the U.S. Army, commercial, industrial, and consumer operators are each pursuing technologies that will enable Condition-Based Maintenance (CBM) of ground vehicles. Conventional maintenance schedules for ground vehicles are determined based on reliability predictions of a population of vehicles under anticipated operational loads. Most common vehicle faults occur in the tires, brakes, suspensions, body chassis, and frames. However, despite prediction models, component damage for such vehicles often lies in the tails of the reliability distribution curve. For example, a certain group of vehicles may be deployed to operate on a harsh terrain that is particularly taxing on the mechanical components of those vehicles. The reliability predictions for these vehicles may not accurately predict component issues. Not surprisingly, operation and support costs for military vehicles account for a large portion of budget cost.
To ensure readiness and decrease these costs for ground vehicle fleets, health monitoring technologies are being developed to assess the reliability of the fleet. Some fleets have health monitoring systems installed within each vehicle to enhance the reliability predictions. However, individual health monitoring systems for each vehicle may be expensive.
Some conventional health monitoring systems evaluate the health of the vehicle based on the dynamic responses of the vehicle as it traverses over terrain. One way of detecting faults in mechanical components is to detect anomalies in comparisons between measured vibrations and healthy reference signatures. In order to make this comparison, a library of vibration signatures must be developed and categorized according to the operational conditions of the vehicle.
There are a number of difficulties with these conventional approaches. The operational responses of the vehicles are difficult to model due to the non-stationary nature of the loading and the inability to control these loads during operation. Second, many vehicles are not equipped with sensors nor the acquisition systems to acquire, process, and store data; therefore, to implement health monitoring for condition-based maintenance, one needs to overcome the economic and technical barriers associated with equipping ground vehicles to continuously monitor their responses. Another difficulty of these health monitoring systems is the limited usefulness of the dynamic response data gathered from the vehicles.
Accordingly, it is desirable to provide health monitoring systems and methods that can be more reliable, require less equipment installed on the vehicles, provide more useful data, and enable modeling of the vehicle's remaining useful life (RUL). Furthermore, other desirable features and characteristics of the present invention will become apparent from the subsequent detailed description of the invention and the appended claims, taken in conjunction with the accompanying drawings and this background of the invention.